Neural networks are for example used in the fields of image recognition or classification, for example for signposts, for the indexing of large image databases, for the recognition of post codes on an envelope or more generally for the recognition of alphanumeric characters.
But the invention also applies to any other application which requires the use of a processor and of a storage memory in order to carry out operations on digitally sampled signals. The envisaged signals can be image, video, audio signals, and also radiofrequency signals.
The problem envisaged by the invention consists in quantizing a real signal on the lowest possible number of bits so as to limit the resources needed to store the signal samples and carry out the mathematical operations needed for the envisaged processings with the simplest possible embodiment in regard to hardware. In particular, the invention is aimed at allowing a simplification in the structure for multiplying two real numbers.
But the quantization of the signal must also make it possible not to degrade the performance and the precision of the processings applied to the signals.
The literature in the field of neural networks comprises teachings relating to the possible solutions for reducing the complexity of the processings carried out within the framework of applications of this type.
Reference [1] presents an optimization of the multiplication operations and other nonlinear operations used in the processings executed by neural networks. The envisaged optimization consists in performing a linear approximation of an integer number. For example the number 2x is approximated by 2int(x)(1+frac(x)), where int(x) designates the integer part of the real number x and frac(x) designates its fractional part. The implementation of a multiplication of two numbers approximated by this representation requires only the use of shift registers and adders. However, the multiplication operation remains complex to implement.
Reference [2] proposes to use an approximate representation of the exact multiplication operation by introducing an iterative logarithmic multiplier. However, the number of bits used to quantize the real numbers is not optimized.
The invention proposes to solve the limitations of the prior art solutions by proposing a procedure for quantizing a real signal which uses a particular approximation and which makes it possible to simplify the implementation of the operation of multiplying two real numbers.